1 June 2005 An algorithm for unsupervised unmixing of hyperspectral imagery using positive matrix factorization
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Abstract
This paper presents an approach for simultaneous determination of endmembers and their abundances in hyperspectral imagery using a constrained positive matrix factorization. The algorithm presented here solves the constrained PMF by formulating it as a nonnegative least squares problem where the cost function is expanded with a penalty term to enforce the sum to one constraint. Preliminary results using simulated and AVIRIS-Cuprite data are presented. These results show the potential of the method to solve the unsupervised unmixing problem.
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Yahya M. Masalmah, Yahya M. Masalmah, Miguel Velez-Reyes, Miguel Velez-Reyes, Samuel Rosario-Torres, Samuel Rosario-Torres, } "An algorithm for unsupervised unmixing of hyperspectral imagery using positive matrix factorization", Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.605672; https://doi.org/10.1117/12.605672
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